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Updated in [April 24th, 2023]

This course provides an overview of advanced portfolio construction and analysis with Python. Students will learn the estimation of risk and return parameters for meaningful portfolio decisions, as well as a variety of state-of-the-art portfolio construction techniques. Lecture videos will cover the theory and math, while students will also have the opportunity to code along with the instructor to gain a deep and practical understanding of how those methods work. By the end of the course, students will have a foundational understanding of modern computational methods in investment management, as well as practical mastery in the implementation of those methods.

[Applications]
Upon completion of this course, students will have a foundational understanding of modern computational methods in investment management and practical mastery in the implementation of those methods. They will have a powerful toolkit to perform their own analysis and build their own implementations, and will be able to use their newly acquired knowledge to improve on current methods.

[Career Paths]
Recommended Career Paths:

1. Investment Analyst: Investment analysts are responsible for researching and analyzing financial data to make informed investment decisions. They use their knowledge of financial markets and economic trends to identify potential investments and assess their risk and return potential. Investment analysts must have a strong understanding of portfolio construction and analysis techniques, as well as the ability to interpret and analyze financial data. As the financial industry continues to evolve, investment analysts must stay up to date on the latest trends and technologies to remain competitive.

2. Quantitative Analyst: Quantitative analysts use mathematical and statistical models to analyze financial data and make predictions about future market movements. They must have a strong understanding of portfolio construction and analysis techniques, as well as the ability to interpret and analyze financial data. Quantitative analysts must also be able to develop and implement their own models and algorithms to identify potential investments and assess their risk and return potential. As the financial industry continues to evolve, quantitative analysts must stay up to date on the latest trends and technologies to remain competitive.

3. Risk Manager: Risk managers are responsible for identifying, assessing, and managing risks associated with investments. They must have a strong understanding of portfolio construction and analysis techniques, as well as the ability to interpret and analyze financial data. Risk managers must also be able to develop and implement their own models and algorithms to identify potential risks and assess their impact on investments. As the financial industry continues to evolve, risk managers must stay up to date on the latest trends and technologies to remain competitive.

4. Portfolio Manager: Portfolio managers are responsible for managing portfolios of investments. They must have a strong understanding of portfolio construction and analysis techniques, as well as the ability to interpret and analyze financial data. Portfolio managers must also be able to develop and implement their own models and algorithms to identify potential investments and assess their risk and return potential. As the financial industry continues to evolve, portfolio managers must stay up to date on the latest trends and technologies to remain competitive.

[Education Paths]
Recommended Degree Paths:
1. Master of Science in Financial Engineering: This degree program focuses on the application of quantitative methods to the analysis and management of financial markets and investments. It combines the study of mathematics, economics, and computer science to develop the skills necessary to analyze and manage financial risk. Students learn to use mathematical models to analyze financial markets, develop strategies for portfolio management, and design and implement financial instruments. This degree is becoming increasingly popular as the financial industry continues to rely more heavily on quantitative methods.

2. Master of Science in Computational Finance: This degree program focuses on the application of computer science and mathematics to the analysis and management of financial markets and investments. It combines the study of mathematics, economics, and computer science to develop the skills necessary to analyze and manage financial risk. Students learn to use mathematical models to analyze financial markets, develop strategies for portfolio management, and design and implement financial instruments. This degree is becoming increasingly popular as the financial industry continues to rely more heavily on quantitative methods.

3. Master of Science in Investment Management: This degree program focuses on the application of financial theory and analysis to the management of investments. It combines the study of economics, finance, and accounting to develop the skills necessary to analyze and manage investments. Students learn to use financial models to analyze investments, develop strategies for portfolio management, and design and implement investment strategies. This degree is becoming increasingly popular as the financial industry continues to rely more heavily on quantitative methods.

4. Master of Science in Quantitative Finance: This degree program focuses on the application of quantitative methods to the analysis and management of financial markets and investments. It combines the study of mathematics, economics, and computer science to develop the skills necessary to analyze and manage financial risk. Students learn to use mathematical models to analyze financial markets, develop strategies for portfolio management, and design and implement financial instruments. This degree is becoming increasingly popular as the financial industry continues to rely more heavily on quantitative methods.